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ColossalAI/colossalai/context/process_group_initializer/initializer_tensor.py

45 lines
1.6 KiB

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#!/usr/bin/env python
# -*- encoding: utf-8 -*-
import torch.distributed as dist
from colossalai.registry import DIST_GROUP_INITIALIZER
from .process_group_initializer import ProcessGroupInitializer
from ..parallel_mode import ParallelMode
@DIST_GROUP_INITIALIZER.register_module
class Initializer_Tensor(ProcessGroupInitializer):
"""A ProcessGroupInitializer for tensor parallelism.
:param args: Args used to initialize ProcessGroupInitializer
:param kwargs: Kwargs used to initialize ProcessGroupInitializer
"""
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def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.num_tensor_parallel_group = self.world_size // self.tensor_parallel_size
def init_dist_group(self):
"""Initialize tensor parallel groups, and assign local_ranks and groups to each gpu.
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:return: Tensor parallelism's information
:rtype: Tuple(local_rank, group_world_size, process_group, ranks_in_group, mode)
"""
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local_rank = None
ranks_in_group = None
process_group = None
group_world_size = None
mode = ParallelMode.TENSOR
for i in range(self.num_tensor_parallel_group):
ranks = [i * self.tensor_parallel_size + j for j in range(self.tensor_parallel_size)]
group = dist.new_group(ranks)
if self.rank in ranks:
local_rank = ranks.index(self.rank)
group_world_size = len(ranks)
process_group = group
ranks_in_group = ranks
return local_rank, group_world_size, process_group, ranks_in_group, mode